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Do cigarette producers price-discriminate by state? An empirical analysis of local cigarette pricing and taxation
J O ~
OF
E C 0 1 ELSEVIER
Journal of Health Economics 15 (1996) 499-512
Do cigarette producers price-discriminate by state? An empirical analysis of local cigarette pricing and taxation Theodore E. Keeler a.*, Teh-wei Hu b Paul G. Barnett c Willard G. Manning a, Hai-Yen Sung e
9
a Department of Economics, University of California, Berkeley, CA 94720-3880, USA b School of Public Health, Universi~ of California, Berkeley, CA 94720-7360, USA c Center for Health Care Evaluation, US Department of Veterans Administration Medical Center, Menlo Park, CA, USA School of Public Health, Division of Health Science Research and Policy, Universi~ of Minnesota, Minnesota, MN 55455-0392, USA e The Permanente Medical Group, Department ofQuali~ and Utilization, Oakland, CA, USA
Received 1 April 1994; accepted 1 April 1996
Abstract This study analyzes the interactive effects of oligopoly pricing, state taxation, and anti-smoking regulations on retail cigarette prices by state, using panel data for the 50 US states between 1960 and 1990. The results indicate that cigarette producers do price-discriminate by state, though the effect is not large relative to the final retail price. There are two further results: (1) state taxes are more than passed on - a 1-cent state tax increase results in a price increase of 1.11 cents, and (2) sellers offset state and local anti-smoking laws with lower prices, thereby blunting effects of the regulations. JEL classification: D43; H71; I 18; L66 Keywords: Tobacco; Cigarettes; Oligopoly; Taxation
* Corresponding author. Tel: 510-642-4411 ; Fax: 510-642-6615. 0167-6296/96/$15.00 Copyright © 1996 Elsevier Science B.V, All rights reserved. PH S0167- 6 2 9 6 ( 9 6 ) 0 0 4 9 8 - 5
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1. Introduction Tobacco taxes have an important impact on cigarette consumption. Most previous analysis of tobacco taxation has emphasized the demand side, i.e. the effects of price on demand 1. However, to analyze the effects of a tax, it is necessary to combine the supply response of the selling firms and the demand response of consumers. Although some supply models have been developed 2, there is still much remaining work to be done using a single, integrated model of producer and consumer behavior 3. In this paper, we develop such a model and estimate it using a panel of state data for the years 1960-1990. Although the effects of Federal taxes have been dealt with elsewhere (Sung et al., 1994; Barnett et al., 1995), there remains the crucial unanswered question as to whether cigarette manufacturers are able to price-discriminate by state, depending on levels of state taxes and on interstate variations in costs and demand. It is to that specific issue that the present paper is addressed. Additionally, we develop theoretically and test empirically a new hypothesis implied by regional price discrimination: that sellers will, to some degree, offset the effects of anti-smoking laws with lower prices. The first section of this paper presents our model. It differs from some previous models in that it does not treat the ability to discriminate locally as equivalent to national market power for manufacturers. The second section describes the data sources and estimation techniques and presents the results. It also discusses the implications of our analysis for tax and regulatory policies, and applies the analysis to consider the effects of large state tax changes. The third section summarizes our conclusions and suggests further research.
2. The model In order to test statistically the hypothesis of price discrimination by state, we must derive two alternative models, one that does not allow such discrimination, and one that allows it. Both views have had their advocates in the literature. Based on careful observation of the industry, Tennant (1950) claimed that all wholesalers faced the same price, independent of location (except for freight and local taxes), even though the industry is a tight oligopoly: "Wholesale prices of standard brand cigarettes have been ... consistently uniform and rigid ... all jobbers have usually received all standard brands at exactly the same delivered price" (p. 274). Those
J For a summary up to 1987, see Harris (1987). More recent examples include Chaloupka (1991), Wasserman et al. (1991), Keeler et al. (1993) and Becker et al. (1994). 2 Recent examples include Sumner (1981), Bishop and Yoo (1985), Sullivan (1985), Porter (1986), Roberts and Samuelson (1988) and Showalter (1991). 3 One recent analysis of these issues, based on national time-series data for the U.S., is Barnett et al. (1995). Another, working with panel data for the Western U.S., with a somewhat different pricing model, is Sung et al. (1994).
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in agreement with Tennant might argue that the trend toward less local discrimination would have become more pronounced in recent years, given the growth of national chains of discount stores, such as Walmart. Such firms should be able to negotiate a single wholesale price for their cigarettes, independent of the state in which the cigarettes are sold. Indeed, by 1987, 28% of the value of shipments of US cigarette manufacturers (or 24% of the amount sold by wholesalers) was sold directly from the wholesale branches of the manufacturing firms to retailers, without intervening wholesalers 4. Furthermore, attempted restraint of trade at the level required to discriminate by state may be illegal under the Robinson-Patman Act 5. A final argument in support of Tennant's conclusion is that profit-maximizing wholesalers would be irrational to fail to take advantage of arbitrage opportunities: there is evidence that the largest wholesalers are quite large in size, relative both to the tobacco manufacturers and to total sales in many states, all of which suggests that the manufacturers may have difficulty enforcing price discrimination on the wholesalers and preventing arbitrage 6. On the other hand, Sumner (198 l) has argued that cigarette wholesalers are often prevented by state laws from arbitraging across state lines, making price discrimination by state quite feasible on the part of cigarette manufacturers, at least to the extent that they have monopoly power at the manufacturing level. There may of course be some truth to both Sumner's and Tennant's assertions: there could be market power for manufacturers at both the national (nondiscriminatory) and the state (discriminatory) levels. We therefore develop alternative models that do and do not allow for price discrimination by state. 2.1. A model with no price discrimination
For this model, we first assume monopolistic behavior and then incorporate oligopoly subsequently. We assume that the inverse demand curve for cigarettes in
4 Sales offices of the manufacturers were responsible for $5.88 billion dollars in sales of tobacco products, without other wholesalers being involved. See US Bureau of the Census (1987a, vol. I, p. 1-139). On the other hand, the total value of shipments of tobacco product manufacturing plants was about $20.76 billion (US Bureau of the Census, 1987b, vol. 1, general summary, p. 1-5). The value of sales by wholesalers was $25 billion (US Bureau of the Census, 1987a, p. !-139). 5 Interregional price discrimination on the part of manufacturers selling to wholesalers has been illegal since the passage of the Robinson-Patman Act of 1936, For a summary of the cases, see Scherer and Ross (1990, pp. 508-516). An extreme and illustrative example described there is Utah Pie (1967), in which a baker was forced to pay treble damages, having been found to charge different prices for wholesale pies in California and Utah. 6 The total value of wholesale tobacco sales in the U.S. in 1987 was just over $25 billion, or just over $4 billion per manufacturing firm on average (see US Bureau of the Census, 1987a, vol. 1, p. 1-139). On the other hand, total sales by the top four nonmanufacturer wholesalers (merchant wholesalers) was $4.1 billion, or about $1 billion per firm. These top four wholesalers owned 116 wholesale establishments, over 29 establishments per firm. Given that many states have total sales under $t billion, and fewer than 29 wholesale establishments, it would seem clear that many wholesalers operate on an interstate basis.
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each state is linear and proportional to the adult (smoking-age) population of that state 7. There is a state tax for state i, t~; at this point, we exclude both Federal taxes and distribution costs, which are incorporated below. Therefore, for each adult in state i, the inverse demand curve is: P = a - t i -- bqi
( 1)
The total demand in each state will be Qi = ni( a / b - t i / b -
P/b)
(2)
where n; is the total adult population of state i. The aggregate, nationwide demand curve which would be faced by a monopolistic cigarette producer will equal Q= ~iQi = ~i[ni°t/b-
niti/b-
niP~b]
(3)
We can rewrite Eq. (3) as O = U~r/b- Xt/b-
UP/b
(4)
where N is the total adult population of the US (as Eini = N ) and the bold t is the population-weighted average state tax rate over all states. The nationwide inverse demand curve is then P= t~-t-
Q( b / N )
(5)
Thus, we find that a monopolistic producer will maximize profits based on a nationwide demand curve that treats the population-weighted average state tax rate as if it were a Federal tax 8. If the marginal costs 9 are constant at the value c, then the profit-maximization problem faced by a monopolistic tobacco firm would be to maximize 1r= Q( a -
t - B Q ) - cQ
(6)
where B = b / N , for notational convenience. To maximize this, we differentiate (6) with respect to Q, set that expression equal to 0, and solve for Q. The resulting profit-maximizing monopoly quantity is then Qm=-(a-t-c)/2B
(7)
7 The simplest rationale for this assumption is that the portion of smokers in the total adult population is constant, and that each smoker has a linear demand curve. However, a more general and realistic assumption would be that the demand curve incorporates both prevalence and amount of smoking, and that it is dependent on the size of the adult population. 8 Note, however, that if the Federal tax is uniform nationwide, the monopolistic producer could easily be the collector of the tax, whereas the state portion of the tax would be collected at a more locaI level and not by the producing firm. The same is true of distribution costs. The implications of this difference for the estimated price equation are discussed below. 9 This is a reasonable approximation to reality; see Barnett et al. (1995), which contains empirical estimation of a translog cost function for cigarette production in the U.S.
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and the profit-maximizing (average) monopoly price, inclusive of state taxes, is
em =0.5(
+ t + o)
(s)
Now suppose that there is a distribution cost for each state i of
D i = D + d~
(9)
where D is a fixed component and d i is the component (e.g. transportation costs) that varies by state. If there is a Federal excise cigarette tax of tf, then it can easily be shown that the price equation, inclusive of state and Federal taxes and distribution costs is Pm = 0.5(
+ D+
tf+t +d+O)
10)
where d is the weighted average of the state-specific distribution costs ~0. The wholesale price charged by the monopolist, exclusive of state and local taxes and distribution costs, is therefore ~"
P m w = O . 5 ( a + D + tf + t + d + c ) - ( D + t + d ) =0.5(a-
O + tf-t-d
+ c)
(11) (12)
It is next worth considering how Eq. (12) would change if we analyze a tight oligopoly, such as the cigarette industry, rather than a monopoly. Perhaps the most plausible assumption is the very general one that the observed market price will be a function of both the monopoly price and the concentration ratio. This model was originally proposed by Bain (1951) and Chamberlin (1962), but has been developed in a more current theoretical model by Sutton (1991). The model assumes that the sellers in a tight oligopoly would like to arrive at a cooperative, joint-profit-maximizing solution, but are hampered from doing so by the fact that the industry is neither a monopoly, nor are collusive agreements enforceable. Under these circumstances, coordination becomes more difficult as concentration becomes lower. Under these assumptions, the observed oligopoly price will approach the monopoly price as concentration becomes higher, and it will approach the competitive price as concentration becomes lower 12
10 To see this, note from above that the portion of the distribution cost invariant to distance D i and the Federal tax tf are both equivalent to additions to marginal cost for the monopolist. Furthermore, the state-specific distribution cost d i is conceptually equivalent to the state tax t i. i i Note that we are assuming that the producing firm is assigned the task of collecting the Federal tax and paying it to the Federal government. In that sense, the Federal tax functions as if it were a marginal manufacturing cost to the producing firm. On the other hand, the producing firm cannot collect state and local taxes. Thus, they are not included in the wholesale 'price' collected by the monopolistic seller. 12 Note that this outcome is similar to that of the Cournot model with or without conjectural variations, but its behavioral assumptions are somewhat different.
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Therefore, we propose to approximate the relationship between the observed price P ~ and the monopoly price, P* = ~ , P m H °
(13)
where H is the Herfindahl concentration statistic (scaled such that for a monopoly, H = 1) for the industry and 0 is a positive constant. In order to estimate our price equation with oligopoly behavior, we must deal with another crucial issue, that is, whether the tobacco oligopoly attempts to coordinate prices around after-tax prices or before-tax prices. For Federal taxes, and for distribution costs which do not vary by state or distance, it is reasonable to assume that the tobacco oligopoly attempts to treat them as a cost and coordinates them, as in the case of a monopoly; the Federal tax is paid as cigarettes are shipped. However, for this simple case, the oligopoly is not able to price-discriminate locally. Thus, we assume that the oligopoly does not coordinate around state taxes and state-specific distribution costs. Based on these assumptions, we can rewrite Eq. (12), the retail monopoly price actually paid in state i, as Pmi = O'5( a - D + tf + c - t - d ) + ti + d i
(14)
and we can characterize the after-tax, retail price in state i as follows. Substituting Eq. (13) into Eq. (14), we have Pi* = 0 . 5 ( A + t f - - t + C) t~lI"I ° h- t i q- d i
(15)
where A = a + D - d . 2.2. A m o d e l with p r i c e discrimination
Now we consider what happens when manufacturers are free to price-discriminate between states. In this case, the monopolist will treat the tax and distribution cost for each state as a cost for purposes of profit-maximizing. To make the model more general, we will consider what will happen if for each state a is not constant, but is rather a function allowed to vary with various demographic attributes of that state. Thus, a = t~(X), where X is a vector of taste variables, such as religion, socioeconomic status, etc. Then the retail monopoly price equation will be P d m i = O . 5 ( a ( X ) + tf + C + t i + d i )
(16)
based on the same analysis as above. Incorporating oligopoly price-coordination assumption from Eq. (13), we have the retail oligopoly price: P d m i = - 0 . 5 ( o t ( X ) + tf + c + t i + d i ) 6 , H °
(17)
Finally, previous studies (such as Becker et al., 1994) find that demand curves for cigarettes have shifted over time. Given the dramatic changes in tastes which
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have occurred over time, we also allow the price equation to have a different constant for each year. Because the Federal tax, Herfindahl, and marginal production cost variables vary only over time, the interaction variables in Eq. (17) between H and the tax and production cost variables are not identified if we include year dummies; they, along with the demand constant, are subsumed into annual dummies. However, the terms relating to the interaction term between H ° and the state tax and distribution cost variables are identified, because the tax and distribution cost variables are different over different states, and H interacts with them nonlinearly. Thus, by estimating Eq. (17) with annual dummy variables, it is possible to test the hypothesis of interstate price discrimination. If there is discrimination, 0 will be significant, as will the demand variables. If Tennant's hypothesis is right, 0 and the demand variables will not differ significantly from zero, but the state tax variable will have a coefficient of one (if there were perfect competition and constant returns to scale in wholesaling and retailing). Unfortunately, it is not possible to test the equally important hypothesis that there is monopoly pricing at the wholesale level that goes beyond local discrimination, as suggested by Tennant, because of the above-mentioned collinearity with the annual dummy variables. Still, testing the local price discrimination hypothesis is a worthwhile goal in itself. To estimate Eq. (17) with available data, there are some additional points worth noting. First, to better control for variations in distribution and retail costs, we include variables for average real wholesale and retail wages by state and year, and distance (a proxy for transport costs) from Durham, North Carolina, to the largest city in each state. To further test for interstate price discrimination in the model we included in the price equation variables that affect demand and costs in each state in Eq. (17) in such a way as to affect the local price. In Eq. (17), anything that shifts the inverse demand equation, such as state-specific factors in o~, will also affect the state-specific price. If the firms are unable to price-discriminate, stateAevel variables only enter via the grand mean, as in Eq. (14). One such demand variable is anti-smoking regulations and ordinances that prevail in states and localities. If these regulations and ordinances are effective, they should lower the intercept of the demand curve. Thus, more stringent regulations will induce sellers to offset the effects of those regulations with lower prices. Such an effect, if it occurs, will obviously reduce the desired effects of the regulations. To test for this hypothesis, we include a variable for state and local regulations in the price equation 13
13 This variable was calculated from Pertschuk and Shopland (1989). based on the weights set forth for each level of stringency in Warner (1981).
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Another state-specific demand variable that should affect price is a 'bootlegging' variable accounting for ease of imports or exports by the consumers in a given state. If there is interstate price discrimination, consumers may find an opportunity for informal arbitrage if they live close to the state's border with a lower-priced state. Thus, the price in a given state may be responsive to these variables. In other words, the population of a state being able to save money by crossing state lines may result in more elastic demand, and hence a lower price-cost margin, all other things being equal. Similarly, lack of opportunity to bootleg will entail a less elastic demand, and hence a higher price-cost margin, again ceteris paribus. Our measure of the attractiveness of bootlegging incorporates combined measures of the fraction of the population living near the state border and the savings (if any) which can be had by crossing the state border to buy cigarettes. Traditionally, one can incorporate separate indices of attractiveness of imports and exports for each state. However, Becket et al. (1994) have shown theoretically that it is unnecessary to include both indices in a demand equation or a reduced-form price equation; one index will suffice. Therefore, we include an index of export attractiveness, EXPINDX, which was developed by Barnett (1993, pp. 64-71). In addition, we include other variables often found in previous studies (Becker et al., 1994; Sung et al., 1994). These include real income, the percentage of the population divorced, the percentage of the population female, revenue for hotel services (indicating outside travelers in the state), the percentage of the population that is high school and college graduates, the unemployment rate (the unemployed tend to smoke more), the percentage of the population that is elderly (the elderly tend to smoke less), ethnic variables (percentage African and Native American), and religious variables (percentage Baptist, Roman Catholic, and Mormon). Given the strong Mormon strictures against smoking, one would expect the last variable to be negative. These considerations suggest the following specification for Eq. (17):
Pit = Yo + H°(Ylti, + EffljEijt + EktrkXikt) + Et ~,Dit
(18)
where the value of the parameter Y0 is the value of the constant term for the year lacking a dummy variable (1990), as defined above, t is the state tax rate for a given year and state, Eij t is the distribution and retail cost variables described above, Xik , is the other demand shifters, and D, is the annual dummy variables, to 14 account for changes in taste
14 N o state fixed effects are included; they conflict with the identification o f the tax effects o f concern to us.
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507
3. Estimation and results Estimation of Eq. (18) was by nonlinear least squares, using state panel data 15 for the years 1960-1990. We have treated all right-hand variables in our analysis as exogenous, because all those relevant to hypotheses at issue here are arguably 16 exogenous Our results (Table 1) are consistent with the hypothesis of local price discrimination. The state tax and Herfindahl coefficients are positive and significant, as are practically all the local cost and demand coefficients. This confirms the hypothesis that there is price discrimination by state. Thus among demand variables, more women and elderly in the population reduce price, as do more stringent state and local anti-smoking laws. On the other hand, higher income, more African Americans, Native Americans, divorced, unemployed, Baptists and Catholics in the population increased the price, as did more hotel revenues. The coefficient for the Mormon variable is implausible, because it implies that the demand intercept rises with more Mormons. The coefficients for high school and college education are both positive, though the high school coefficient is insignificant. Among the cost variables, a higher freight cost, higher retail and wholesale costs all cause higher
15 The sources of the data are as follows: Quantity of cigarettes consumed, and Federal and state taxes (which include state estimates of average local taxes), Tobacco Institute (1991). Populations of persons over 15 (used to calculate consumption per adult) come from US Bureau of the Census (1960. 1970, 1980, 1990), with exponential interpolations for intermediate years. Socioeconomic variables (African American, Native American, age, gender, employment, and marital status) come from these same census sources. To convert to real prices, we used the national US Consumer Price Index (Bureau of Labor Statistics, various years). Mileages from Durham, NC come from Rand McNally (1992). The Herfindahl index is calculated from Advertising Age, various issues. Wholesale and retail trade data come from the US Bureau of the Census (1963, 1968, 1972, 1977, 1982, 1987a,1992), with exponential interpolation used to fill in intervening years. Retail wages are expressed here as a fraction of total retail costs. Wholesale costs include both wages and estimated interest costs on tobacco inventories. Details of calculations are shown in Barnett (1993). Data on religions (Baptist, Catholic, and Mormon) are from Whitman and Trimble (1956), Johnson et al. (1974), Quinn et al. (1982) and Bradley et al. (1992). Exponential interpolations were done for years for which data were not available. State and local anti-smoking regulation numbers are calculated in the same way as Warner (19811 and Wasserman et al. (199t), using data from Pertschuk and Shopland (1989). To calculate state averages for local ordinances, population weights were used, with exponential interpolations for non-census years. 16 It can be strongly argued that all the variables included in the price equation are exogenous. Poterba (1994) makes the strong argument that state tax policies date back many decades, and can be treated as exogenous for purposes of cross-sectional analysis. Furthermore, short-run shifts in taxes are driven by a state's broad financial needs, rather than by changes in the cigarette market. The Federal tax has been changed very few times in nominal terms, and it, too, has a strongly exogenous quality. If there is controversy around the exogeneity of a variable in this analysis, it is with the Herfindahl statistic (for pros and cons as to its exogeneity, see Scherer and Ross (1990, ch. l 1). However, the present analysis is not directly concerned with the analysis of what is exogenous in oligopoly behavior, but rather with controlling for its effects in analyzing the effects of taxation. We would argue that the present specification is appropriate for those purposes.
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Table 1 Regression results: the price equation - nonlinear least squares Parameter
Estimate
t-statistic
Constant
102.5920
I 1.62
S t a t e tax
0.6636
9,91
Freight cost
4.4286
3.03
- 0.2172
- 2,17 3.55
Export index Real per capita income
0.0989
Retail wage costs
0,1553
1.36
Wholesale cost
0.1147
3.50
Fraction divorced Fraction female
7.8706
i. 14
- 20.2707
- 2.28
Fraction military
0.0752
1.02
Fraction Mormon
1.7771
2.40
Real hotel revenues
1.4799
5.47
Fraction college educated
0.0388
2.10
Fraction Baptist
2.0978
1.64
Fraction Catholic
0.8489
1.21
Fraction unemployed
0,2715
5.58
4.0171
1.07
Local anti-smoking ordinances
Fraction Native American
- 2.8289
- 2,75
State anti-smoking laws
-0.2704
- 1.40
Fraction high school educated F r a c t i o n o v e r 65
2.9557 -8,8160
1.19 - 1.98
Fraction African American
3.2878
H e r f i n d a h l statistic
0.6039
5.00
- 28.1442
- 9.23
1960 dummy 1961 d u m m y
- 27.3044
1962 d u m m y
-29.3833
3.37
- 9.50 - 10.35
! 963 dummy
- 28.7907
- 10.13
1964 dummy
- 30.3675
- 10.59
1965 d u m m y
- 27.8715
- 9.68
1966 dummy
- 29.8443
- 10.14
1967 d u m m y
- 26.0814
- 8.80
1968 d u m m y
- 29.3224
- 9.92
1969 dummy
- 26.4695
- 9.05
1970 dummy
- 29.1416
- I 0.23
1971 d u m m y
- 31.4939
- 11.19
1972 d u m m y
- 34.6558
- 12.32
1973 d u m m y
- 35.7790
- 12.96
1974 dummy 1975 d u m m y
- 36.9933 - 37,8090
- 14.32 - 15.62
1976 dummy 1977 d u m m y
- 39.3789 - 34,1230
- 17.03 - 15.30
1978 d u m m y t979 dummy
- 35.9540 - 38.0715
- 16,84 - 18.74
1980 dummy
- 42.5974
- 23.10
1981 d u m m y
-41.0661
- 24.57
1982 dummy 1983 d u m m y
-- 3 4 . 7 9 6 4 -26.2249
- 22,97 - 17.51
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509
Table 1 (continued) 1984 d u m m y
- 24.4958
1985 d u m m y
-21.7854
- 17,79
1986 dummy
- 18.8388
- 17,89
1987 d u m m y
- 15.5955
- 16,99
1988 d u m m y
- 1 t.0345
- 13.45
1989 d u m m y
- 5.48375
Adjusted R-squared
- 18.08
- 7.15 0.9209
prices; these cost results are consistent with both discriminatory and nondiscriminatory pricing. There are three further questions we would like to consider. First, what fraction of state taxes is passed on to consumers? Second, how 'important' is this local market power, in the sense of how much variation in local price do observed variations in the Herfindahl statistic cause? Third, how large are the price effects of the anti-smoking regulation variable? 3. I. Incidence of state taxes For a given value of concentration ( H ) in Eq. (18), there is a linear relationship between state taxes and price. We calculated the effects of a l-cent increase in the state tax on price, and this was done for each observation in the sample (varying by H). The results indicated that a marginal state tax is more than passed on by a minimum of 3% to a maximum of 26%, with a mean of 11%, based on the approximation in Eq. (13). Although this value is lower than some previous estimates (Sung et al., 1994), it is higher than the theory predicts with a flat distribution supply curve and either no price discrimination by state (all passed on) or monopoly discrimination with a linear demand curve (half passed on). Furthermore, a test for statistical significance on the mean value of 1.11 indicates that it is significantly different from 1.00 at the 0.001 level r7 3.2. Effects of variations in market power A clearer way to get a sense of the importance of local price discrimination is to determine how much price would vary compared with what it currently is if H were at minimum or maximum values observed in our sample. Results of this analysis indicate that varying H in that way would change retail prices by anywhere from 1.1 to 2.0%. By this measure, the degree of local price discrimination would not seem to be high.
~7 U s i n g t h e delta m e t h o d , w e f i n d a t-statistic o f 6 . 0 2 o n t h e test as to w h e t h e r t h e p a s s - t h r o u g h c o e f f i c i e n t m i n u s o n e d i f f e r s f r o m zero.
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3.3. Offsetting effects o f price changes relative to anti-smoking regulations Conceptually, it is possible that most of the effects of anti-smoking laws could be offset by lower prices charged in states and localities that have such regulations. The results on anti-smoking laws are mixed. More stringent laws reduce the price, but the effect of state laws is not significantly different from zero. Both our state and our local anti-smoking law variables are scaled between 0 for no regulations and 1 for the most stringent. One method of analyzing their potential effects (similar to Wasserman et al., 1991) is to consider movement from values of 0.25 (mild regulations) to 1 (the most stringent observed). Results of these simulations with state anti-smoking regulations (whose effect is in any event not significant) indicate a decrease in price of 0.3 to 0.4 cents, compared with a mean price of 94.1 cents. On the other hand, a similar exercise with local ordinances indicates a price decrease of 3.3 to 4 cents, a more substantial amount. However, except for very few states in only a few years in the 1980s, the local ordinance variable was at or near 0. How well this price behavior would extrapolate nationwide if many more local governments passed anti-smoking ordinances is unclear. Furthermore, there are no available demand studies showing reliable direct effects of local ordinances on cigarette consumption, so it is impossible to determine how much this price effect offsets the desired effects of the laws 18 This offset effect could be a significant force in blunting the effects of anti-smoking laws, but further research and more precise estimates are needed to determine whether this is so.
4. Conclusions The present study differs from previous ones in that it explicitly incorporates a model of oligopoly pricing behavior into the analysis of the impact of taxation on retail cigarette prices by state. It also allows for a direct test of the hypothesis that cigarette manufacturers price-discriminate by state, through use of a specification by which the national Herfindahl statistic interacts with determinants of price by state. The results confirm the hypothesis of local price discrimination, finding it to be statistically quite significant. However, the overall effect does not appear to be extremely large - varying the Herfindahl between the lowest and highest values changes the final price by 1.3 to 2%. All other things being equal, a 1-cent-per-pack increase in a given state tax appears to be more than passed on: it results in a 1.11 cent increase in the final cigarette price.
t8 With the inclusion of time dummies or trend variables, as here, neither Keeler et al. (1993) nor Sung et al. (1994) find significant effects for anti-smoking laws on demand. Attempts at estimating demand equations with this data set resulted in the same outcome. Wasserman et al. (1991) work only with state anti-smoking laws, so their results cannot be used for comparison with those shown here.
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A new result in this paper, derived theoretically and confirmed statistically, is that state and local anti-smoking laws may to some degree be offset by sellers responding to the resulting shifts in demand lowering retail prices. Although this result is statistically significant for local ordinances, the extent to which it offsets the effects of the laws is a subject requiring further research.
Acknowledgements The authors acknowledge the support of the California Tobacco-Related Disease Project (Award RT-12) and, for final work on the paper, the Robert Wood Johnson Substance Abuse Policy Research Program, both through the Institute of Business and Economic Research at the University of California. They also acknowledge the very helpful comments of Michael Grossman, Joseph Newhouse, and an anonymous referee. The referee was especially helpful in highlighting the potential for our study to test hypotheses concerning local price discrimination.
References Bain, J.S., 195t, Relationship of profit rate to industry concentration: American manufacturing, 1936-1940, Quarterly Journal of Economics 65, 293-324. Barnett, P.G., 1993, Excise taxes, oligopoly coordination, and the advent of discount cigarette brands, Doctoral dissertation (University of California, Berkeley). Barnett, P.G., T.E. Keeler and T. Hu, 1995, Oligopoly structure and the incidence of cigarette excise taxes, Journal of Public Economics 57, 457-470. Bradley, M.B., N.M. Green, D.E. Jones, M. Lynn and L. McNeil, 1992, Churches and church membership in the United States, 1990 (Glenmary Research Center, Atlanta, GA), Becket, GS., M. Grossman and K. Murphy, 1994, An empirical analysis of cigarette addiction, American Economic Review 84, 396-418. Bishop, J.A. and J.H. Yoo, 1985, 'Health scare', excise taxes, and advertising ban in cigarette demand and supply, Southern Economic Journal 52, 402-411. Chaloupka, F.J., 1991, Rational addictive behavior and cigarette smoking, Journal of Political Economy 99, 722-742. Chamberlin, E.H., 1962, The theory of monopolistic competition: a re-orientation of the theory, of value, 8th ed. (Harvard University Press, Cambridge). Harris, J.E., 1987, The 1983 increase in the federal cigarette excise tax, in L.H. Summers, ed., Tax policy and the economy (NBER and MIT Press Journals, Cambridge) 1, 87-111. Johnson, D.W., P,R. Picard and B. Quinn, 1974, Churches and church membership in the United States, 1971 (Glenmary Research Center, Atlanta, GA). Keeler, T., T. Hu, P. Barnett and W. Manning, 1993, Taxation, regulation, and addiction: a demand function for cigarettes based on time-series evidence, Journal of Health Economics 12, 1-18. Pertschuk, M. and D.R. Shopland, 1989, Major local smoking ordinances in the United States (Americans for Nonsmokers' Rights, Berkeley). Porter, R.H., 1986, The impact of government policy on the US cigarette industry, in P. Ippolito and 13. Scheffman, eds., Empirical approaches to consumer protection economics (Bureau of Economics, Federal Trade Commission, Washington) 447-481.
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Poterba, J.M., 1994, State responses to fiscal crises: the effects of budgetary institutions and politics, Journal of Political Economy 102, 799-821. Quinn, B , H. Anderson, M. Bradley, P. Getting and P. Shriver, 1982, Churches and church membership in the United States, 1980 (Glenmary Research Center, Atlanta, GA). Rand McNally, 1992, Rand McNally road atlas (Rand McNally, New York). Roberts, M.J. and L. Samuelson, 1988, An empirical analysis of dynamic, nonprice competition in an oligopolistic industry, Rand Journal of Economics 19, 200-220. Scherer, F.M. and D. Ross, 1990, Industrial market structure and economic performance (Houghton Mifflin, Boston). Showalter, M.H., 1991, Monopoly behavior with intertemporal demands, Working Paper (Department of Economics, Brigham Young University, Provo, Utah). Sullivan, D., 1985, Testing hypotheses about firm behavior in the cigarette industry, Journal of Political Economy 93, 586-598. Sumner, D., 1981, Measurement of monopoly behavior: an application to the cigarette industry, Journal of Political Economy 89, 1010-1019. Sung, H.-Y., T. Hu, and T.E. Keeler, 1994, Cigarette taxation, demand, and producer behavior: an empirical model, Contemporary Economic Policy 7, 91-100. Sutton, J., 1991, Sunk costs and market structure (Massachusetts Institute of Technology Press, Cambridge, MA). Tennant, R.B,, t 950, The American cigarette industry: a study in economic analysis and public policy (Yale University Press, New Haven). Tobacco Institute, 1991, The tax burden on tobacco: historical compilation, 1990 (Tobacco Institute, Washington). US Bureau of the Census, 1960, Census of population (US Government Printing Office, Washington). US Bureau of the Census, 1963, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, 1968, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, 1970, Census of population (US Government Printing Office, Washington). US Bureau of the Census, 1972, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, 1977, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, I980, Census of population (US Government Printing Office, Washington). US Bureau of the Census, 1982, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, 1987a, Census of wholesale trade and retail trade (US Government Printing Office, Washington). US Bureau of the Census, 1987b, US Census of Manufacturing, 1987 (US Government Printing Office, Washington). US Bureau of the Census, 1990, Census of population (US Government Printing Office, Washington). US Bureau of the Census, t992, Census of wholesale trade and retail trade (US Government Printing Office, Washington). Warner, K.E., 1981, Cigarette smoking in the 1970s: the impact of anti-smoking campaigns on consumption, Science 211,729-731. Wassennan, J., W.G. Manning, J.P. Newhouse and J.D. Winkler, 1991, The effects of excise taxes and regulations on teenage cigarette smoking, Journal of Health Economics 10, 43-64, Whitman, L,B. and G,W. Trimble, 1956, Churches and church membership in the United States, 1956 (National Council for Churches of Christ, Washington, DC).
OF
E C 0 1 ELSEVIER
Journal of Health Economics 15 (1996) 499-512
Do cigarette producers price-discriminate by state? An empirical analysis of local cigarette pricing and taxation Theodore E. Keeler a.*, Teh-wei Hu b Paul G. Barnett c Willard G. Manning a, Hai-Yen Sung e
9
a Department of Economics, University of California, Berkeley, CA 94720-3880, USA b School of Public Health, Universi~ of California, Berkeley, CA 94720-7360, USA c Center for Health Care Evaluation, US Department of Veterans Administration Medical Center, Menlo Park, CA, USA School of Public Health, Division of Health Science Research and Policy, Universi~ of Minnesota, Minnesota, MN 55455-0392, USA e The Permanente Medical Group, Department ofQuali~ and Utilization, Oakland, CA, USA
Received 1 April 1994; accepted 1 April 1996
Abstract This study analyzes the interactive effects of oligopoly pricing, state taxation, and anti-smoking regulations on retail cigarette prices by state, using panel data for the 50 US states between 1960 and 1990. The results indicate that cigarette producers do price-discriminate by state, though the effect is not large relative to the final retail price. There are two further results: (1) state taxes are more than passed on - a 1-cent state tax increase results in a price increase of 1.11 cents, and (2) sellers offset state and local anti-smoking laws with lower prices, thereby blunting effects of the regulations. JEL classification: D43; H71; I 18; L66 Keywords: Tobacco; Cigarettes; Oligopoly; Taxation
* Corresponding author. Tel: 510-642-4411 ; Fax: 510-642-6615. 0167-6296/96/$15.00 Copyright © 1996 Elsevier Science B.V, All rights reserved. PH S0167- 6 2 9 6 ( 9 6 ) 0 0 4 9 8 - 5
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1. Introduction Tobacco taxes have an important impact on cigarette consumption. Most previous analysis of tobacco taxation has emphasized the demand side, i.e. the effects of price on demand 1. However, to analyze the effects of a tax, it is necessary to combine the supply response of the selling firms and the demand response of consumers. Although some supply models have been developed 2, there is still much remaining work to be done using a single, integrated model of producer and consumer behavior 3. In this paper, we develop such a model and estimate it using a panel of state data for the years 1960-1990. Although the effects of Federal taxes have been dealt with elsewhere (Sung et al., 1994; Barnett et al., 1995), there remains the crucial unanswered question as to whether cigarette manufacturers are able to price-discriminate by state, depending on levels of state taxes and on interstate variations in costs and demand. It is to that specific issue that the present paper is addressed. Additionally, we develop theoretically and test empirically a new hypothesis implied by regional price discrimination: that sellers will, to some degree, offset the effects of anti-smoking laws with lower prices. The first section of this paper presents our model. It differs from some previous models in that it does not treat the ability to discriminate locally as equivalent to national market power for manufacturers. The second section describes the data sources and estimation techniques and presents the results. It also discusses the implications of our analysis for tax and regulatory policies, and applies the analysis to consider the effects of large state tax changes. The third section summarizes our conclusions and suggests further research.
2. The model In order to test statistically the hypothesis of price discrimination by state, we must derive two alternative models, one that does not allow such discrimination, and one that allows it. Both views have had their advocates in the literature. Based on careful observation of the industry, Tennant (1950) claimed that all wholesalers faced the same price, independent of location (except for freight and local taxes), even though the industry is a tight oligopoly: "Wholesale prices of standard brand cigarettes have been ... consistently uniform and rigid ... all jobbers have usually received all standard brands at exactly the same delivered price" (p. 274). Those
J For a summary up to 1987, see Harris (1987). More recent examples include Chaloupka (1991), Wasserman et al. (1991), Keeler et al. (1993) and Becker et al. (1994). 2 Recent examples include Sumner (1981), Bishop and Yoo (1985), Sullivan (1985), Porter (1986), Roberts and Samuelson (1988) and Showalter (1991). 3 One recent analysis of these issues, based on national time-series data for the U.S., is Barnett et al. (1995). Another, working with panel data for the Western U.S., with a somewhat different pricing model, is Sung et al. (1994).
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in agreement with Tennant might argue that the trend toward less local discrimination would have become more pronounced in recent years, given the growth of national chains of discount stores, such as Walmart. Such firms should be able to negotiate a single wholesale price for their cigarettes, independent of the state in which the cigarettes are sold. Indeed, by 1987, 28% of the value of shipments of US cigarette manufacturers (or 24% of the amount sold by wholesalers) was sold directly from the wholesale branches of the manufacturing firms to retailers, without intervening wholesalers 4. Furthermore, attempted restraint of trade at the level required to discriminate by state may be illegal under the Robinson-Patman Act 5. A final argument in support of Tennant's conclusion is that profit-maximizing wholesalers would be irrational to fail to take advantage of arbitrage opportunities: there is evidence that the largest wholesalers are quite large in size, relative both to the tobacco manufacturers and to total sales in many states, all of which suggests that the manufacturers may have difficulty enforcing price discrimination on the wholesalers and preventing arbitrage 6. On the other hand, Sumner (198 l) has argued that cigarette wholesalers are often prevented by state laws from arbitraging across state lines, making price discrimination by state quite feasible on the part of cigarette manufacturers, at least to the extent that they have monopoly power at the manufacturing level. There may of course be some truth to both Sumner's and Tennant's assertions: there could be market power for manufacturers at both the national (nondiscriminatory) and the state (discriminatory) levels. We therefore develop alternative models that do and do not allow for price discrimination by state. 2.1. A model with no price discrimination
For this model, we first assume monopolistic behavior and then incorporate oligopoly subsequently. We assume that the inverse demand curve for cigarettes in
4 Sales offices of the manufacturers were responsible for $5.88 billion dollars in sales of tobacco products, without other wholesalers being involved. See US Bureau of the Census (1987a, vol. I, p. 1-139). On the other hand, the total value of shipments of tobacco product manufacturing plants was about $20.76 billion (US Bureau of the Census, 1987b, vol. 1, general summary, p. 1-5). The value of sales by wholesalers was $25 billion (US Bureau of the Census, 1987a, p. !-139). 5 Interregional price discrimination on the part of manufacturers selling to wholesalers has been illegal since the passage of the Robinson-Patman Act of 1936, For a summary of the cases, see Scherer and Ross (1990, pp. 508-516). An extreme and illustrative example described there is Utah Pie (1967), in which a baker was forced to pay treble damages, having been found to charge different prices for wholesale pies in California and Utah. 6 The total value of wholesale tobacco sales in the U.S. in 1987 was just over $25 billion, or just over $4 billion per manufacturing firm on average (see US Bureau of the Census, 1987a, vol. 1, p. 1-139). On the other hand, total sales by the top four nonmanufacturer wholesalers (merchant wholesalers) was $4.1 billion, or about $1 billion per firm. These top four wholesalers owned 116 wholesale establishments, over 29 establishments per firm. Given that many states have total sales under $t billion, and fewer than 29 wholesale establishments, it would seem clear that many wholesalers operate on an interstate basis.
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T.E. Keeler et al./ Journal of Health Economics 15 (1996) 499-512
each state is linear and proportional to the adult (smoking-age) population of that state 7. There is a state tax for state i, t~; at this point, we exclude both Federal taxes and distribution costs, which are incorporated below. Therefore, for each adult in state i, the inverse demand curve is: P = a - t i -- bqi
( 1)
The total demand in each state will be Qi = ni( a / b - t i / b -
P/b)
(2)
where n; is the total adult population of state i. The aggregate, nationwide demand curve which would be faced by a monopolistic cigarette producer will equal Q= ~iQi = ~i[ni°t/b-
niti/b-
niP~b]
(3)
We can rewrite Eq. (3) as O = U~r/b- Xt/b-
UP/b
(4)
where N is the total adult population of the US (as Eini = N ) and the bold t is the population-weighted average state tax rate over all states. The nationwide inverse demand curve is then P= t~-t-
Q( b / N )
(5)
Thus, we find that a monopolistic producer will maximize profits based on a nationwide demand curve that treats the population-weighted average state tax rate as if it were a Federal tax 8. If the marginal costs 9 are constant at the value c, then the profit-maximization problem faced by a monopolistic tobacco firm would be to maximize 1r= Q( a -
t - B Q ) - cQ
(6)
where B = b / N , for notational convenience. To maximize this, we differentiate (6) with respect to Q, set that expression equal to 0, and solve for Q. The resulting profit-maximizing monopoly quantity is then Qm=-(a-t-c)/2B
(7)
7 The simplest rationale for this assumption is that the portion of smokers in the total adult population is constant, and that each smoker has a linear demand curve. However, a more general and realistic assumption would be that the demand curve incorporates both prevalence and amount of smoking, and that it is dependent on the size of the adult population. 8 Note, however, that if the Federal tax is uniform nationwide, the monopolistic producer could easily be the collector of the tax, whereas the state portion of the tax would be collected at a more locaI level and not by the producing firm. The same is true of distribution costs. The implications of this difference for the estimated price equation are discussed below. 9 This is a reasonable approximation to reality; see Barnett et al. (1995), which contains empirical estimation of a translog cost function for cigarette production in the U.S.
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503
and the profit-maximizing (average) monopoly price, inclusive of state taxes, is
em =0.5(
+ t + o)
(s)
Now suppose that there is a distribution cost for each state i of
D i = D + d~
(9)
where D is a fixed component and d i is the component (e.g. transportation costs) that varies by state. If there is a Federal excise cigarette tax of tf, then it can easily be shown that the price equation, inclusive of state and Federal taxes and distribution costs is Pm = 0.5(
+ D+
tf+t +d+O)
10)
where d is the weighted average of the state-specific distribution costs ~0. The wholesale price charged by the monopolist, exclusive of state and local taxes and distribution costs, is therefore ~"
P m w = O . 5 ( a + D + tf + t + d + c ) - ( D + t + d ) =0.5(a-
O + tf-t-d
+ c)
(11) (12)
It is next worth considering how Eq. (12) would change if we analyze a tight oligopoly, such as the cigarette industry, rather than a monopoly. Perhaps the most plausible assumption is the very general one that the observed market price will be a function of both the monopoly price and the concentration ratio. This model was originally proposed by Bain (1951) and Chamberlin (1962), but has been developed in a more current theoretical model by Sutton (1991). The model assumes that the sellers in a tight oligopoly would like to arrive at a cooperative, joint-profit-maximizing solution, but are hampered from doing so by the fact that the industry is neither a monopoly, nor are collusive agreements enforceable. Under these circumstances, coordination becomes more difficult as concentration becomes lower. Under these assumptions, the observed oligopoly price will approach the monopoly price as concentration becomes higher, and it will approach the competitive price as concentration becomes lower 12
10 To see this, note from above that the portion of the distribution cost invariant to distance D i and the Federal tax tf are both equivalent to additions to marginal cost for the monopolist. Furthermore, the state-specific distribution cost d i is conceptually equivalent to the state tax t i. i i Note that we are assuming that the producing firm is assigned the task of collecting the Federal tax and paying it to the Federal government. In that sense, the Federal tax functions as if it were a marginal manufacturing cost to the producing firm. On the other hand, the producing firm cannot collect state and local taxes. Thus, they are not included in the wholesale 'price' collected by the monopolistic seller. 12 Note that this outcome is similar to that of the Cournot model with or without conjectural variations, but its behavioral assumptions are somewhat different.
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Therefore, we propose to approximate the relationship between the observed price P ~ and the monopoly price, P* = ~ , P m H °
(13)
where H is the Herfindahl concentration statistic (scaled such that for a monopoly, H = 1) for the industry and 0 is a positive constant. In order to estimate our price equation with oligopoly behavior, we must deal with another crucial issue, that is, whether the tobacco oligopoly attempts to coordinate prices around after-tax prices or before-tax prices. For Federal taxes, and for distribution costs which do not vary by state or distance, it is reasonable to assume that the tobacco oligopoly attempts to treat them as a cost and coordinates them, as in the case of a monopoly; the Federal tax is paid as cigarettes are shipped. However, for this simple case, the oligopoly is not able to price-discriminate locally. Thus, we assume that the oligopoly does not coordinate around state taxes and state-specific distribution costs. Based on these assumptions, we can rewrite Eq. (12), the retail monopoly price actually paid in state i, as Pmi = O'5( a - D + tf + c - t - d ) + ti + d i
(14)
and we can characterize the after-tax, retail price in state i as follows. Substituting Eq. (13) into Eq. (14), we have Pi* = 0 . 5 ( A + t f - - t + C) t~lI"I ° h- t i q- d i
(15)
where A = a + D - d . 2.2. A m o d e l with p r i c e discrimination
Now we consider what happens when manufacturers are free to price-discriminate between states. In this case, the monopolist will treat the tax and distribution cost for each state as a cost for purposes of profit-maximizing. To make the model more general, we will consider what will happen if for each state a is not constant, but is rather a function allowed to vary with various demographic attributes of that state. Thus, a = t~(X), where X is a vector of taste variables, such as religion, socioeconomic status, etc. Then the retail monopoly price equation will be P d m i = O . 5 ( a ( X ) + tf + C + t i + d i )
(16)
based on the same analysis as above. Incorporating oligopoly price-coordination assumption from Eq. (13), we have the retail oligopoly price: P d m i = - 0 . 5 ( o t ( X ) + tf + c + t i + d i ) 6 , H °
(17)
Finally, previous studies (such as Becker et al., 1994) find that demand curves for cigarettes have shifted over time. Given the dramatic changes in tastes which
T.E. Keeler et al. / Journal of Health Economics 15 (1996) 499-512
505
have occurred over time, we also allow the price equation to have a different constant for each year. Because the Federal tax, Herfindahl, and marginal production cost variables vary only over time, the interaction variables in Eq. (17) between H and the tax and production cost variables are not identified if we include year dummies; they, along with the demand constant, are subsumed into annual dummies. However, the terms relating to the interaction term between H ° and the state tax and distribution cost variables are identified, because the tax and distribution cost variables are different over different states, and H interacts with them nonlinearly. Thus, by estimating Eq. (17) with annual dummy variables, it is possible to test the hypothesis of interstate price discrimination. If there is discrimination, 0 will be significant, as will the demand variables. If Tennant's hypothesis is right, 0 and the demand variables will not differ significantly from zero, but the state tax variable will have a coefficient of one (if there were perfect competition and constant returns to scale in wholesaling and retailing). Unfortunately, it is not possible to test the equally important hypothesis that there is monopoly pricing at the wholesale level that goes beyond local discrimination, as suggested by Tennant, because of the above-mentioned collinearity with the annual dummy variables. Still, testing the local price discrimination hypothesis is a worthwhile goal in itself. To estimate Eq. (17) with available data, there are some additional points worth noting. First, to better control for variations in distribution and retail costs, we include variables for average real wholesale and retail wages by state and year, and distance (a proxy for transport costs) from Durham, North Carolina, to the largest city in each state. To further test for interstate price discrimination in the model we included in the price equation variables that affect demand and costs in each state in Eq. (17) in such a way as to affect the local price. In Eq. (17), anything that shifts the inverse demand equation, such as state-specific factors in o~, will also affect the state-specific price. If the firms are unable to price-discriminate, stateAevel variables only enter via the grand mean, as in Eq. (14). One such demand variable is anti-smoking regulations and ordinances that prevail in states and localities. If these regulations and ordinances are effective, they should lower the intercept of the demand curve. Thus, more stringent regulations will induce sellers to offset the effects of those regulations with lower prices. Such an effect, if it occurs, will obviously reduce the desired effects of the regulations. To test for this hypothesis, we include a variable for state and local regulations in the price equation 13
13 This variable was calculated from Pertschuk and Shopland (1989). based on the weights set forth for each level of stringency in Warner (1981).
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Another state-specific demand variable that should affect price is a 'bootlegging' variable accounting for ease of imports or exports by the consumers in a given state. If there is interstate price discrimination, consumers may find an opportunity for informal arbitrage if they live close to the state's border with a lower-priced state. Thus, the price in a given state may be responsive to these variables. In other words, the population of a state being able to save money by crossing state lines may result in more elastic demand, and hence a lower price-cost margin, all other things being equal. Similarly, lack of opportunity to bootleg will entail a less elastic demand, and hence a higher price-cost margin, again ceteris paribus. Our measure of the attractiveness of bootlegging incorporates combined measures of the fraction of the population living near the state border and the savings (if any) which can be had by crossing the state border to buy cigarettes. Traditionally, one can incorporate separate indices of attractiveness of imports and exports for each state. However, Becket et al. (1994) have shown theoretically that it is unnecessary to include both indices in a demand equation or a reduced-form price equation; one index will suffice. Therefore, we include an index of export attractiveness, EXPINDX, which was developed by Barnett (1993, pp. 64-71). In addition, we include other variables often found in previous studies (Becker et al., 1994; Sung et al., 1994). These include real income, the percentage of the population divorced, the percentage of the population female, revenue for hotel services (indicating outside travelers in the state), the percentage of the population that is high school and college graduates, the unemployment rate (the unemployed tend to smoke more), the percentage of the population that is elderly (the elderly tend to smoke less), ethnic variables (percentage African and Native American), and religious variables (percentage Baptist, Roman Catholic, and Mormon). Given the strong Mormon strictures against smoking, one would expect the last variable to be negative. These considerations suggest the following specification for Eq. (17):
Pit = Yo + H°(Ylti, + EffljEijt + EktrkXikt) + Et ~,Dit
(18)
where the value of the parameter Y0 is the value of the constant term for the year lacking a dummy variable (1990), as defined above, t is the state tax rate for a given year and state, Eij t is the distribution and retail cost variables described above, Xik , is the other demand shifters, and D, is the annual dummy variables, to 14 account for changes in taste
14 N o state fixed effects are included; they conflict with the identification o f the tax effects o f concern to us.
T.E. Keeler et al. / Journal of Health Economics 15 (I996) 499 512
507
3. Estimation and results Estimation of Eq. (18) was by nonlinear least squares, using state panel data 15 for the years 1960-1990. We have treated all right-hand variables in our analysis as exogenous, because all those relevant to hypotheses at issue here are arguably 16 exogenous Our results (Table 1) are consistent with the hypothesis of local price discrimination. The state tax and Herfindahl coefficients are positive and significant, as are practically all the local cost and demand coefficients. This confirms the hypothesis that there is price discrimination by state. Thus among demand variables, more women and elderly in the population reduce price, as do more stringent state and local anti-smoking laws. On the other hand, higher income, more African Americans, Native Americans, divorced, unemployed, Baptists and Catholics in the population increased the price, as did more hotel revenues. The coefficient for the Mormon variable is implausible, because it implies that the demand intercept rises with more Mormons. The coefficients for high school and college education are both positive, though the high school coefficient is insignificant. Among the cost variables, a higher freight cost, higher retail and wholesale costs all cause higher
15 The sources of the data are as follows: Quantity of cigarettes consumed, and Federal and state taxes (which include state estimates of average local taxes), Tobacco Institute (1991). Populations of persons over 15 (used to calculate consumption per adult) come from US Bureau of the Census (1960. 1970, 1980, 1990), with exponential interpolations for intermediate years. Socioeconomic variables (African American, Native American, age, gender, employment, and marital status) come from these same census sources. To convert to real prices, we used the national US Consumer Price Index (Bureau of Labor Statistics, various years). Mileages from Durham, NC come from Rand McNally (1992). The Herfindahl index is calculated from Advertising Age, various issues. Wholesale and retail trade data come from the US Bureau of the Census (1963, 1968, 1972, 1977, 1982, 1987a,1992), with exponential interpolation used to fill in intervening years. Retail wages are expressed here as a fraction of total retail costs. Wholesale costs include both wages and estimated interest costs on tobacco inventories. Details of calculations are shown in Barnett (1993). Data on religions (Baptist, Catholic, and Mormon) are from Whitman and Trimble (1956), Johnson et al. (1974), Quinn et al. (1982) and Bradley et al. (1992). Exponential interpolations were done for years for which data were not available. State and local anti-smoking regulation numbers are calculated in the same way as Warner (19811 and Wasserman et al. (199t), using data from Pertschuk and Shopland (1989). To calculate state averages for local ordinances, population weights were used, with exponential interpolations for non-census years. 16 It can be strongly argued that all the variables included in the price equation are exogenous. Poterba (1994) makes the strong argument that state tax policies date back many decades, and can be treated as exogenous for purposes of cross-sectional analysis. Furthermore, short-run shifts in taxes are driven by a state's broad financial needs, rather than by changes in the cigarette market. The Federal tax has been changed very few times in nominal terms, and it, too, has a strongly exogenous quality. If there is controversy around the exogeneity of a variable in this analysis, it is with the Herfindahl statistic (for pros and cons as to its exogeneity, see Scherer and Ross (1990, ch. l 1). However, the present analysis is not directly concerned with the analysis of what is exogenous in oligopoly behavior, but rather with controlling for its effects in analyzing the effects of taxation. We would argue that the present specification is appropriate for those purposes.
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Table 1 Regression results: the price equation - nonlinear least squares Parameter
Estimate
t-statistic
Constant
102.5920
I 1.62
S t a t e tax
0.6636
9,91
Freight cost
4.4286
3.03
- 0.2172
- 2,17 3.55
Export index Real per capita income
0.0989
Retail wage costs
0,1553
1.36
Wholesale cost
0.1147
3.50
Fraction divorced Fraction female
7.8706
i. 14
- 20.2707
- 2.28
Fraction military
0.0752
1.02
Fraction Mormon
1.7771
2.40
Real hotel revenues
1.4799
5.47
Fraction college educated
0.0388
2.10
Fraction Baptist
2.0978
1.64
Fraction Catholic
0.8489
1.21
Fraction unemployed
0,2715
5.58
4.0171
1.07
Local anti-smoking ordinances
Fraction Native American
- 2.8289
- 2,75
State anti-smoking laws
-0.2704
- 1.40
Fraction high school educated F r a c t i o n o v e r 65
2.9557 -8,8160
1.19 - 1.98
Fraction African American
3.2878
H e r f i n d a h l statistic
0.6039
5.00
- 28.1442
- 9.23
1960 dummy 1961 d u m m y
- 27.3044
1962 d u m m y
-29.3833
3.37
- 9.50 - 10.35
! 963 dummy
- 28.7907
- 10.13
1964 dummy
- 30.3675
- 10.59
1965 d u m m y
- 27.8715
- 9.68
1966 dummy
- 29.8443
- 10.14
1967 d u m m y
- 26.0814
- 8.80
1968 d u m m y
- 29.3224
- 9.92
1969 dummy
- 26.4695
- 9.05
1970 dummy
- 29.1416
- I 0.23
1971 d u m m y
- 31.4939
- 11.19
1972 d u m m y
- 34.6558
- 12.32
1973 d u m m y
- 35.7790
- 12.96
1974 dummy 1975 d u m m y
- 36.9933 - 37,8090
- 14.32 - 15.62
1976 dummy 1977 d u m m y
- 39.3789 - 34,1230
- 17.03 - 15.30
1978 d u m m y t979 dummy
- 35.9540 - 38.0715
- 16,84 - 18.74
1980 dummy
- 42.5974
- 23.10
1981 d u m m y
-41.0661
- 24.57
1982 dummy 1983 d u m m y
-- 3 4 . 7 9 6 4 -26.2249
- 22,97 - 17.51
T.E. Keeler et aL / Journal of Health Economics 15 (1996) 499-512
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Table 1 (continued) 1984 d u m m y
- 24.4958
1985 d u m m y
-21.7854
- 17,79
1986 dummy
- 18.8388
- 17,89
1987 d u m m y
- 15.5955
- 16,99
1988 d u m m y
- 1 t.0345
- 13.45
1989 d u m m y
- 5.48375
Adjusted R-squared
- 18.08
- 7.15 0.9209
prices; these cost results are consistent with both discriminatory and nondiscriminatory pricing. There are three further questions we would like to consider. First, what fraction of state taxes is passed on to consumers? Second, how 'important' is this local market power, in the sense of how much variation in local price do observed variations in the Herfindahl statistic cause? Third, how large are the price effects of the anti-smoking regulation variable? 3. I. Incidence of state taxes For a given value of concentration ( H ) in Eq. (18), there is a linear relationship between state taxes and price. We calculated the effects of a l-cent increase in the state tax on price, and this was done for each observation in the sample (varying by H). The results indicated that a marginal state tax is more than passed on by a minimum of 3% to a maximum of 26%, with a mean of 11%, based on the approximation in Eq. (13). Although this value is lower than some previous estimates (Sung et al., 1994), it is higher than the theory predicts with a flat distribution supply curve and either no price discrimination by state (all passed on) or monopoly discrimination with a linear demand curve (half passed on). Furthermore, a test for statistical significance on the mean value of 1.11 indicates that it is significantly different from 1.00 at the 0.001 level r7 3.2. Effects of variations in market power A clearer way to get a sense of the importance of local price discrimination is to determine how much price would vary compared with what it currently is if H were at minimum or maximum values observed in our sample. Results of this analysis indicate that varying H in that way would change retail prices by anywhere from 1.1 to 2.0%. By this measure, the degree of local price discrimination would not seem to be high.
~7 U s i n g t h e delta m e t h o d , w e f i n d a t-statistic o f 6 . 0 2 o n t h e test as to w h e t h e r t h e p a s s - t h r o u g h c o e f f i c i e n t m i n u s o n e d i f f e r s f r o m zero.
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3.3. Offsetting effects o f price changes relative to anti-smoking regulations Conceptually, it is possible that most of the effects of anti-smoking laws could be offset by lower prices charged in states and localities that have such regulations. The results on anti-smoking laws are mixed. More stringent laws reduce the price, but the effect of state laws is not significantly different from zero. Both our state and our local anti-smoking law variables are scaled between 0 for no regulations and 1 for the most stringent. One method of analyzing their potential effects (similar to Wasserman et al., 1991) is to consider movement from values of 0.25 (mild regulations) to 1 (the most stringent observed). Results of these simulations with state anti-smoking regulations (whose effect is in any event not significant) indicate a decrease in price of 0.3 to 0.4 cents, compared with a mean price of 94.1 cents. On the other hand, a similar exercise with local ordinances indicates a price decrease of 3.3 to 4 cents, a more substantial amount. However, except for very few states in only a few years in the 1980s, the local ordinance variable was at or near 0. How well this price behavior would extrapolate nationwide if many more local governments passed anti-smoking ordinances is unclear. Furthermore, there are no available demand studies showing reliable direct effects of local ordinances on cigarette consumption, so it is impossible to determine how much this price effect offsets the desired effects of the laws 18 This offset effect could be a significant force in blunting the effects of anti-smoking laws, but further research and more precise estimates are needed to determine whether this is so.
4. Conclusions The present study differs from previous ones in that it explicitly incorporates a model of oligopoly pricing behavior into the analysis of the impact of taxation on retail cigarette prices by state. It also allows for a direct test of the hypothesis that cigarette manufacturers price-discriminate by state, through use of a specification by which the national Herfindahl statistic interacts with determinants of price by state. The results confirm the hypothesis of local price discrimination, finding it to be statistically quite significant. However, the overall effect does not appear to be extremely large - varying the Herfindahl between the lowest and highest values changes the final price by 1.3 to 2%. All other things being equal, a 1-cent-per-pack increase in a given state tax appears to be more than passed on: it results in a 1.11 cent increase in the final cigarette price.
t8 With the inclusion of time dummies or trend variables, as here, neither Keeler et al. (1993) nor Sung et al. (1994) find significant effects for anti-smoking laws on demand. Attempts at estimating demand equations with this data set resulted in the same outcome. Wasserman et al. (1991) work only with state anti-smoking laws, so their results cannot be used for comparison with those shown here.
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A new result in this paper, derived theoretically and confirmed statistically, is that state and local anti-smoking laws may to some degree be offset by sellers responding to the resulting shifts in demand lowering retail prices. Although this result is statistically significant for local ordinances, the extent to which it offsets the effects of the laws is a subject requiring further research.
Acknowledgements The authors acknowledge the support of the California Tobacco-Related Disease Project (Award RT-12) and, for final work on the paper, the Robert Wood Johnson Substance Abuse Policy Research Program, both through the Institute of Business and Economic Research at the University of California. They also acknowledge the very helpful comments of Michael Grossman, Joseph Newhouse, and an anonymous referee. The referee was especially helpful in highlighting the potential for our study to test hypotheses concerning local price discrimination.
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